BSP has been researched extensively in the past with applications spanning a variety of areas including autonomous navigation, multi-modal planning, and active SLAM [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}.[7]} consider object uncertainty since they are planning in an unknown environment
and require several measurements to obtain confidence estimates of object locations. Thus they perform active perception, that is, to look for robot actions that enhances information to reduce the object uncertainty. This context is different from ours since we consider a known environment with object uncertainty and focus on active localization incorporating these uncertainties. In [8]}, the concept of object uncertainty is commented upon (they call it scene uncertainty); however they do not show how it affects the state estimation. Dynamic environments are considered in [2]}, [3]} however the landmark/beacon locations are assumed to be known perfectly; [5]}, [6]} also consider perfect landmark locations in the context of task and motion planning. Thus most active and passive localization-based approaches focus on robot state uncertainty and assume perfect knowledge about the location of the objects in the environment. However, in practice, the environment is seldom known with high certainty and hence providing formal guarantees for safe navigation is imperative.
